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Learning to define an electrical biomarker of the epileptogenic zone
The role of fast activity as a potential biomarker in localization of the epileptogenic zone (EZ) remains controversial due to recently reported unsatisfactory performance. We recently identified a “fingerprint” of the EZ as a time‐frequency pattern that is defined by a combination of preictal spike...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley & Sons, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268034/ https://www.ncbi.nlm.nih.gov/pubmed/31609058 http://dx.doi.org/10.1002/hbm.24813 |
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author | Li, Jian Grinenko, Olesya Mosher, John C. Gonzalez‐Martinez, Jorge Leahy, Richard M. Chauvel, Patrick |
author_facet | Li, Jian Grinenko, Olesya Mosher, John C. Gonzalez‐Martinez, Jorge Leahy, Richard M. Chauvel, Patrick |
author_sort | Li, Jian |
collection | PubMed |
description | The role of fast activity as a potential biomarker in localization of the epileptogenic zone (EZ) remains controversial due to recently reported unsatisfactory performance. We recently identified a “fingerprint” of the EZ as a time‐frequency pattern that is defined by a combination of preictal spike(s), fast oscillatory activity, and concurrent suppression of lower frequencies. Here we examine the generalizability of the fingerprint in application to an independent series of patients (11 seizure‐free and 13 non‐seizure‐free after surgery) and show that the fingerprint can also be identified in seizures with lower frequency (such as beta) oscillatory activity. In the seizure‐free group, only 5 of 47 identified EZ contacts were outside the resection. In contrast, in the non‐seizure‐free group, 104 of 142 identified EZ contacts were outside the resection. We integrated the fingerprint prediction with the subject's MR images, thus providing individualized anatomical estimates of the EZ. We show that these fingerprint‐based estimates in seizure‐free patients are almost always inside the resection. On the other hand, for a large fraction of the nonseizure‐free patients the estimated EZ was not well localized and was partially or completely outside the resection, which may explain surgical failure in such cases. We also show that when mapping fast activity alone onto MR images, the EZ was often over‐estimated, indicating a reduced discriminative ability for fast activity relative to the full fingerprint for localization of the EZ. |
format | Online Article Text |
id | pubmed-7268034 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | John Wiley & Sons, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72680342020-06-12 Learning to define an electrical biomarker of the epileptogenic zone Li, Jian Grinenko, Olesya Mosher, John C. Gonzalez‐Martinez, Jorge Leahy, Richard M. Chauvel, Patrick Hum Brain Mapp Research Articles The role of fast activity as a potential biomarker in localization of the epileptogenic zone (EZ) remains controversial due to recently reported unsatisfactory performance. We recently identified a “fingerprint” of the EZ as a time‐frequency pattern that is defined by a combination of preictal spike(s), fast oscillatory activity, and concurrent suppression of lower frequencies. Here we examine the generalizability of the fingerprint in application to an independent series of patients (11 seizure‐free and 13 non‐seizure‐free after surgery) and show that the fingerprint can also be identified in seizures with lower frequency (such as beta) oscillatory activity. In the seizure‐free group, only 5 of 47 identified EZ contacts were outside the resection. In contrast, in the non‐seizure‐free group, 104 of 142 identified EZ contacts were outside the resection. We integrated the fingerprint prediction with the subject's MR images, thus providing individualized anatomical estimates of the EZ. We show that these fingerprint‐based estimates in seizure‐free patients are almost always inside the resection. On the other hand, for a large fraction of the nonseizure‐free patients the estimated EZ was not well localized and was partially or completely outside the resection, which may explain surgical failure in such cases. We also show that when mapping fast activity alone onto MR images, the EZ was often over‐estimated, indicating a reduced discriminative ability for fast activity relative to the full fingerprint for localization of the EZ. John Wiley & Sons, Inc. 2019-10-14 /pmc/articles/PMC7268034/ /pubmed/31609058 http://dx.doi.org/10.1002/hbm.24813 Text en © 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. |
spellingShingle | Research Articles Li, Jian Grinenko, Olesya Mosher, John C. Gonzalez‐Martinez, Jorge Leahy, Richard M. Chauvel, Patrick Learning to define an electrical biomarker of the epileptogenic zone |
title | Learning to define an electrical biomarker of the epileptogenic zone |
title_full | Learning to define an electrical biomarker of the epileptogenic zone |
title_fullStr | Learning to define an electrical biomarker of the epileptogenic zone |
title_full_unstemmed | Learning to define an electrical biomarker of the epileptogenic zone |
title_short | Learning to define an electrical biomarker of the epileptogenic zone |
title_sort | learning to define an electrical biomarker of the epileptogenic zone |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268034/ https://www.ncbi.nlm.nih.gov/pubmed/31609058 http://dx.doi.org/10.1002/hbm.24813 |
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